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Extract, Transform, and Load EDGAR Online Data in Python

The CData Python Connector for EDGAR Online enables you to create ETL applications and pipelines for EDGAR Online data in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for EDGAR Online and the petl framework, you can build EDGAR Online-connected applications and pipelines for extracting, transforming, and loading EDGAR Online data. This article shows how to connect to EDGAR Online with the CData Python Connector and use petl and pandas to extract, transform, and load EDGAR Online data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live EDGAR Online data in Python. When you issue complex SQL queries from EDGAR Online, the driver pushes supported SQL operations, like filters and aggregations, directly to EDGAR Online and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to EDGAR Online Data

Connecting to EDGAR Online data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

  1. Navigate to https://developer.edgar-online.com/ and create an account.
  2. Register a new application and retrieve the AppKey. You should select one of the available Web APIs this application will use like HackPack, Insider Trades or Institutional Ownership.
    Note: HackPack is the most important Web API that an application can use since it supports a large number of endpoints. If you are getting the "Access Denied" error you must create a new app and select the correct Web API which supports the resource you are querying.
  3. After successfully creating a new app, you can access your keys through your "my account" area. Set the AppKey connection property value equal to the Key of your application.

After installing the CData EDGAR Online Connector, follow the procedure below to install the other required modules and start accessing EDGAR Online through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for EDGAR Online Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.edgaronline as mod

You can now connect with a connection string. Use the connect function for the CData EDGAR Online Connector to create a connection for working with EDGAR Online data.

cnxn = mod.connect("AppKey=20dd8ce9904d422ed89ebde1ad40d")

Create a SQL Statement to Query EDGAR Online

Use SQL to create a statement for querying EDGAR Online. In this article, we read data from the Subscriptions entity.

sql = "SELECT Id, Name FROM Subscriptions WHERE SubscriberEmail = 'user@domain.com'"

Extract, Transform, and Load the EDGAR Online Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the EDGAR Online data. In this example, we extract EDGAR Online data, sort the data by the Name column, and load the data into a CSV file.

Loading EDGAR Online Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'subscriptions_data.csv')

In the following example, we add new rows to the Subscriptions table.

Adding New Rows to EDGAR Online

table1 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

etl.appenddb(table1, cnxn, 'Subscriptions')

With the CData Python Connector for EDGAR Online, you can work with EDGAR Online data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the EDGAR Online Python Connector to start building Python apps and scripts with connectivity to EDGAR Online data. Reach out to our Support Team if you have any questions.



Full Source Code


import petl as etl
import pandas as pd
import cdata.edgaronline as mod

cnxn = mod.connect("AppKey=20dd8ce9904d422ed89ebde1ad40d")

sql = "SELECT Id, Name FROM Subscriptions WHERE SubscriberEmail = 'user@domain.com'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'subscriptions_data.csv')

table3 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

etl.appenddb(table3, cnxn, 'Subscriptions')